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Showing 1 to 15 of 21 results Save | Export
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Astivia, Oscar L. Olvera; Zumbo, Bruno D. – Practical Assessment, Research & Evaluation, 2019
Within psychology and the social sciences, Ordinary Least Squares (OLS) regression is one of the most popular techniques for data analysis. In order to ensure the inferences from the use of this method are appropriate, several assumptions must be satisfied, including the one of constant error variance (i.e. homoskedasticity). Most of the training…
Descriptors: Multiple Regression Analysis, Least Squares Statistics, Statistical Analysis, Error of Measurement
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Antonelli, Tomás M.; Olivieri, Alejandro C. – Journal of Chemical Education, 2020
During a short chemometrics course in the seventh semester of the chemistry undergraduate program, students receive a brief theoretical introduction to multivariate calibration, focused on partial least-squares regression as the most commonly employed data processing tool. The theory is complemented with the use of MVC1_R, an easy-to-use software…
Descriptors: Advanced Students, Undergraduate Students, Chemistry, Science Instruction
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Tellinghuisen, Joel – Journal of Chemical Education, 2016
The method of least squares (LS) yields exact solutions for the adjustable parameters when the number of data values n equals the number of parameters "p". This holds also when the fit model consists of "m" different equations and "m = p", which means that LS algorithms can be used to obtain solutions to systems of…
Descriptors: Least Squares Statistics, Computer Software, Graphs, Chemistry
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Tellinghuisen, Joel – Journal of Chemical Education, 2015
The method of least-squares (LS) has a built-in procedure for estimating the standard errors (SEs) of the adjustable parameters in the fit model: They are the square roots of the diagonal elements of the covariance matrix. This means that one can use least-squares to obtain numerical values of propagated errors by defining the target quantities as…
Descriptors: Least Squares Statistics, Error of Measurement, Error Patterns, Chemistry
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Glaser-Opitz, Henrich; Budajová, Kristina – Acta Didactica Napocensia, 2016
The article introduces a software application (MATH) supporting an education of Applied Mathematics, with focus on Numerical Mathematics. The MATH is an easy to use tool supporting various numerical methods calculations with graphical user interface and integrated plotting tool for graphical representation written in Qt with extensive use of Qwt…
Descriptors: Mathematics Education, Computer Software, Computer Assisted Instruction, College Mathematics
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Pinder, Jonathan P. – Decision Sciences Journal of Innovative Education, 2013
Business students taking business analytics courses that have significant predictive modeling components, such as marketing research, data mining, forecasting, and advanced financial modeling, are introduced to nonlinear regression using application software that is a "black box" to the students. Thus, although correct models are…
Descriptors: Spreadsheets, Computer Software, Regression (Statistics), Business Administration Education
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Bryant, Fred B.; Satorra, Albert – Structural Equation Modeling: A Multidisciplinary Journal, 2012
We highlight critical conceptual and statistical issues and how to resolve them in conducting Satorra-Bentler (SB) scaled difference chi-square tests. Concerning the original (Satorra & Bentler, 2001) and new (Satorra & Bentler, 2010) scaled difference tests, a fundamental difference exists in how to compute properly a model's scaling correction…
Descriptors: Statistical Analysis, Structural Equation Models, Goodness of Fit, Least Squares Statistics
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Chen, Fang; Chalhoub-Deville, Micheline – Language Testing, 2014
Newer statistical procedures are typically introduced to help address the limitations of those already in practice or to deal with emerging research needs. Quantile regression (QR) is introduced in this paper as a relatively new methodology, which is intended to overcome some of the limitations of least squares mean regression (LMR). QR is more…
Descriptors: Regression (Statistics), Language Tests, Language Proficiency, Mathematics Achievement
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Reed, B. Cameron – Physics Education, 2010
A freely available, easy-to-use Excel spreadsheet for performing linear least-squares fits for (x, y) data with errors in both coordinates is described. (Contains 1 table and 1 figure.)
Descriptors: Computer Software, Spreadsheets, Science Instruction, Least Squares Statistics
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Beare, R. A. – International Journal of Mathematical Education in Science and Technology, 2008
Professional astronomers use specialized software not normally available to students to determine the rotation periods of asteroids from fragmented light curve data. This paper describes a simple yet accurate method based on Microsoft Excel[R] that enables students to find periods in asteroid light curve and other discontinuous time series data of…
Descriptors: Least Squares Statistics, Astronomy, Computation, Data Analysis
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Keselman, H. J.; Algina, James; Lix, Lisa M.; Wilcox, Rand R.; Deering, Kathleen N. – Psychological Methods, 2008
Standard least squares analysis of variance methods suffer from poor power under arbitrarily small departures from normality and fail to control the probability of a Type I error when standard assumptions are violated. This article describes a framework for robust estimation and testing that uses trimmed means with an approximate degrees of…
Descriptors: Intervals, Testing, Least Squares Statistics, Effect Size
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Glasser, Leslie – Journal of Chemical Education, 2007
Least-squares linear regression is the best of statistics and it is the worst of statistics. The reasons for this paradoxical claim, arising from possible inapplicability of the method and the excessive influence of "outliers", are discussed and substitute regression methods based on median selection, which is both robust and resistant, are…
Descriptors: Regression (Statistics), Least Squares Statistics, Computer Software, Graduate Students
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Cai, Li; Hayes, Andrew F. – Journal of Educational and Behavioral Statistics, 2008
When the errors in an ordinary least squares (OLS) regression model are heteroscedastic, hypothesis tests involving the regression coefficients can have Type I error rates that are far from the nominal significance level. Asymptotically, this problem can be rectified with the use of a heteroscedasticity-consistent covariance matrix (HCCM)…
Descriptors: Least Squares Statistics, Error Patterns, Error Correction, Computation
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Lipovetsky, S. – International Journal of Mathematical Education in Science and Technology, 2007
The dependent variable in a regular linear regression is a numerical variable, and in a logistic regression it is a binary or categorical variable. In these models the dependent variable has varying values. However, there are problems yielding an identity output of a constant value which can also be modelled in a linear or logistic regression with…
Descriptors: Chemistry, Regression (Statistics), Models, Comparative Analysis
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Helms, T. C.; Doetkott, C. – Journal of Natural Resources and Life Sciences Education, 2007
This educational software was developed to aid teachers and students in their understanding of how the process of identifying the most likely quantitative trait loci (QTL) position is determined between two flanking DNA markers. The objective of the software that we developed was to: (1) show how a QTL is mapped to a position on a chromosome using…
Descriptors: Computer Software, Least Squares Statistics, Genetics, Hypothesis Testing
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